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| import os |
| import json |
| import re |
| import copy |
| import pandas as pd |
|
|
| current_file_path = os.path.dirname(os.path.abspath(__file__)) |
| TBL = pd.read_csv( |
| os.path.join(current_file_path, "res/schools.csv"), sep="\t", header=0 |
| ).fillna("") |
| TBL["name_en"] = TBL["name_en"].map(lambda x: x.lower().strip()) |
| GOOD_SCH = json.load(open(os.path.join(current_file_path, "res/good_sch.json"), "r")) |
| GOOD_SCH = set([re.sub(r"[,. &()()]+", "", c) for c in GOOD_SCH]) |
|
|
|
|
| def loadRank(fnm): |
| global TBL |
| TBL["rank"] = 1000000 |
| with open(fnm, "r", encoding="utf-8") as f: |
| while True: |
| line = f.readline() |
| if not line: |
| break |
| line = line.strip("\n").split(",") |
| try: |
| nm, rk = line[0].strip(), int(line[1]) |
| |
| TBL.loc[((TBL.name_cn == nm) | (TBL.name_en == nm)), "rank"] = rk |
| except Exception: |
| pass |
|
|
|
|
| loadRank(os.path.join(current_file_path, "res/school.rank.csv")) |
|
|
|
|
| def split(txt): |
| tks = [] |
| for t in re.sub(r"[ \t]+", " ", txt).split(): |
| if ( |
| tks |
| and re.match(r".*[a-zA-Z]$", tks[-1]) |
| and re.match(r"[a-zA-Z]", t) |
| and tks |
| ): |
| tks[-1] = tks[-1] + " " + t |
| else: |
| tks.append(t) |
| return tks |
|
|
|
|
| def select(nm): |
| global TBL |
| if not nm: |
| return |
| if isinstance(nm, list): |
| nm = str(nm[0]) |
| nm = split(nm)[0] |
| nm = str(nm).lower().strip() |
| nm = re.sub(r"[((][^()()]+[))]", "", nm.lower()) |
| nm = re.sub(r"(^the |[,.&()();;·]+|^(英国|美国|瑞士))", "", nm) |
| nm = re.sub(r"大学.*学院", "大学", nm) |
| tbl = copy.deepcopy(TBL) |
| tbl["hit_alias"] = tbl["alias"].map(lambda x: nm in set(x.split("+"))) |
| res = tbl[((tbl.name_cn == nm) | (tbl.name_en == nm) | tbl.hit_alias)] |
| if res.empty: |
| return |
|
|
| return json.loads(res.to_json(orient="records"))[0] |
|
|
|
|
| def is_good(nm): |
| global GOOD_SCH |
| nm = re.sub(r"[((][^()()]+[))]", "", nm.lower()) |
| nm = re.sub(r"[''`‘’“”,. &()();;]+", "", nm) |
| return nm in GOOD_SCH |
|
|